1 /**
2 * Copyright 2020 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 #include <vector>
17 #include <memory>
18 #include "common/common_test.h"
19 #include "ops/prelu.h"
20 #include "ir/dtype/type.h"
21 #include "ir/value.h"
22 #include "abstract/dshape.h"
23 #include "utils/tensor_construct_utils.h"
24
25 namespace mindspore {
26 namespace ops {
27 class TestPReLU : public UT::Common {
28 public:
TestPReLU()29 TestPReLU() {}
SetUp()30 void SetUp() {}
TearDown()31 void TearDown() {}
32 };
33
TEST_F(TestPReLU,test_ops_prelu1)34 TEST_F(TestPReLU, test_ops_prelu1) {
35 auto prelu = std::make_shared<PReLU>();
36 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{2, 3, 4});
37 auto tensor_w = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3});
38 MS_EXCEPTION_IF_NULL(tensor_x);
39 MS_EXCEPTION_IF_NULL(tensor_w);
40 auto abstract = prelu->Infer({tensor_x->ToAbstract(), tensor_w->ToAbstract()});
41 MS_EXCEPTION_IF_NULL(abstract);
42 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
43 auto shape_ptr = abstract->BuildShape();
44 MS_EXCEPTION_IF_NULL(shape_ptr);
45 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
46 auto shape = shape_ptr->cast<abstract::ShapePtr>();
47 MS_EXCEPTION_IF_NULL(shape);
48 auto shape_vec = shape->shape();
49 auto type = abstract->BuildType();
50 MS_EXCEPTION_IF_NULL(type);
51 EXPECT_EQ(type->isa<TensorType>(), true);
52 auto tensor_type = type->cast<TensorTypePtr>();
53 MS_EXCEPTION_IF_NULL(tensor_type);
54 auto data_type = tensor_type->element();
55 MS_EXCEPTION_IF_NULL(data_type);
56 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32);
57 EXPECT_EQ(shape_vec.size(), 3);
58 EXPECT_EQ(shape_vec[0], 2);
59 EXPECT_EQ(shape_vec[1], 3);
60 EXPECT_EQ(shape_vec[2], 4);
61 }
62
TEST_F(TestPReLU,test_ops_prelu2)63 TEST_F(TestPReLU, test_ops_prelu2) {
64 auto prelu = std::make_shared<PReLU>();
65 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{5, 6, 7, 8});
66 auto tensor_w = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{1});
67 MS_EXCEPTION_IF_NULL(tensor_x);
68 MS_EXCEPTION_IF_NULL(tensor_w);
69 auto abstract = prelu->Infer({tensor_x->ToAbstract(), tensor_w->ToAbstract()});
70 MS_EXCEPTION_IF_NULL(abstract);
71 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
72 auto shape_ptr = abstract->BuildShape();
73 MS_EXCEPTION_IF_NULL(shape_ptr);
74 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
75 auto shape = shape_ptr->cast<abstract::ShapePtr>();
76 MS_EXCEPTION_IF_NULL(shape);
77 auto shape_vec = shape->shape();
78 auto type = abstract->BuildType();
79 MS_EXCEPTION_IF_NULL(type);
80 EXPECT_EQ(type->isa<TensorType>(), true);
81 auto tensor_type = type->cast<TensorTypePtr>();
82 MS_EXCEPTION_IF_NULL(tensor_type);
83 auto data_type = tensor_type->element();
84 MS_EXCEPTION_IF_NULL(data_type);
85 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat16);
86 EXPECT_EQ(shape_vec.size(), 4);
87 EXPECT_EQ(shape_vec[0], 5);
88 EXPECT_EQ(shape_vec[1], 6);
89 EXPECT_EQ(shape_vec[2], 7);
90 EXPECT_EQ(shape_vec[3], 8);
91 }
92 } // namespace ops
93 } // namespace mindspore
94